Mild cognitive impairment is the early stage of several neurodegenerative diseases, such as Alzheimer's. In this work, we address the use of lifelogging as a tool to obtain pictures from a patient's daily life from an egocentric point of view. We propose to use them in combination with serious games as a way to provide a non-pharmacological treatment to improve their quality of life. To do so, we introduce a novel computer vision technique that classifies rich and non rich egocentric images and uses them in serious games. We present results over a dataset composed by 10,997 images, recorded by 7 different users, achieving 79% of F1-score. Our model presents the first method used for automatic egocentric images selection applicable to serious games.
@article{arxiv.1707.08821,
title = {Serious Games Application for Memory Training Using Egocentric Images},
author = {Gabriel Oliveira-Barra and Marc Bolaños and Estefania Talavera and Adrián Dueñas and Olga Gelonch and Maite Garolera},
journal= {arXiv preprint arXiv:1707.08821},
year = {2017}
}